Experience
7 - 12 yrs
Job Location
Bengaluru, India
Vacancy
1
Designation
Senior Artificial Intelligence Engineer
Job Type
ONSITE
Job Description
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Who are we
We are seeking a Senior AI Software Engineer to join our Agentic AI Platform team.
You will \ design, build, and maintain AI\-powered platform services and infrastructure using modern \ GCP technologies.
This role is ideal for someone with a strong development background in \ Python, hands\-on AI\/ML experience, and a passion for building scalable, intelligent \ systems that accelerate developer productivity and enable autonomous Agentic \ workflows.
What You Will Do
\- Design, build, and deploy AI\/ML solutions using GCP Vertex AI, BigQuery ML, and AI \ Platform for model training, deployment, and serving
\- Develop and maintain platform services for AI agent orchestration, RAG pipelines, \ and LLM integration using Python, FastAPI, and Flask
\- Collaborate with cross\-functional teams to support CI\/CD pipelines for ML models, \ GitLab workflows, and MLOps automation
\- Work with GCP services including Cloud Functions, Cloud Run, Data flow, and \ Pub\/Sub to build event\-driven AI architectures
\- Build and optimize data pipelines using BigQuery, Data flow, and Apache Airflow for \ AI model training and inference
\- Contribute to automation, observability, and reliability initiatives for AI systems \ using GCP Cloud Operations and New Relic
\- Lead and mentor team members in AI\/ML engineering best practices, fostering a \ culture of learning and innovation
\- Explore and integrate cutting\-edge AI capabilities (LLMs, vector databases, prompt \ engineering) into platform solutions
\- Develop customized AI solutions and integrations to meet development teams \ requirements, leveraging GCP APIs, SDKs, and LangChain
\- Create technical documentation, tutorials, and training materials to support AI\/ML \ adoption and facilitate knowledge transfer
\- Stay up to date on latest AI\/ML technologies, GCP products, and industry trends, \ serving as a subject matter expert for the organization
\- Analyze existing AI workflows and processes to identify areas for optimization and \ efficiency gains
\- Implement scalable AI systems and tools to automate repetitive tasks, streamline \ ML operations, and enhance developer productivity \ What You Bring (Required)
Requirements
We are seeking a Senior AI Software Engineer to join our Agentic AI Platform team.
You will \ design, build, and maintain AI\-powered platform services and infrastructure using modern \ GCP technologies.
This role is ideal for someone with a strong development background in \ Python, hands\-on AI\/ML experience, and a passion for building scalable, intelligent \ systems that accelerate developer productivity and enable autonomous Agentic \ workflows.
What You Will Do
\- Design, build, and deploy AI\/ML solutions using GCP Vertex AI, BigQuery ML, and AI \ Platform for model training, deployment, and serving
\- Develop and maintain platform services for AI agent orchestration, RAG pipelines, \ and LLM integration using Python, FastAPI, and Flask
\- Collaborate with cross\-functional teams to support CI\/CD pipelines for ML models, \ GitLab workflows, and MLOps automation
\- Work with GCP services including Cloud Functions, Cloud Run, Data flow, and \ Pub\/Sub to build event\-driven AI architectures
\- Build and optimize data pipelines using BigQuery, Data flow, and Apache Airflow for \ AI model training and inference
\- Contribute to automation, observability, and reliability initiatives for AI systems \ using GCP Cloud Operations and New Relic
\- Lead and mentor team members in AI\/ML engineering best practices, fostering a \ culture of learning and innovation
\- Explore and integrate cutting\-edge AI capabilities (LLMs, vector databases, prompt \ engineering) into platform solutions
\- Develop customized AI solutions and integrations to meet development teams \ requirements, leveraging GCP APIs, SDKs, and LangChain
\- Create technical documentation, tutorials, and training materials to support AI\/ML \ adoption and facilitate knowledge transfer
\- Stay up to date on latest AI\/ML technologies, GCP products, and industry trends, \ serving as a subject matter expert for the organization
\- Analyze existing AI workflows and processes to identify areas for optimization and \ efficiency gains
\- Implement scalable AI systems and tools to automate repetitive tasks, streamline \ ML operations, and enhance developer productivity \ What You Bring (Required)
Requirements
Key Responsibilities
7+ years of experience in software development with 3+ years focused on AI\/ML \ engineering, specializing in scalable AI infrastructure and model deployment
\- Expert proficiency in Python for AI\/ML development (TensorFlow, PyTorch)
\- Hands\-on experience with GCP AI\/ML services (Vertex AI, BigQuery ML, AI Platform, \ AutoML)
\- Strong familiarity with MLOps practices, model versioning, and ML pipeline \ orchestration (Airflow, Kubeflow)
\- Experience building and deploying production AI systems including LLM integration, \ RAG architectures, and vector databases
\- Hands\-on experience with Git, Docker, and Kubernetes for containerized ML \ workloads
\- Excellent problem\-solving skills and a proactive attitude toward learning new AI \ technologies \ Nice to Have
\- Experience with LangChain or other LLM orchestration frameworks
\- Knowledge of vector databases and semantic search
\- Experience with Agentic AI frameworks, ReAct patterns, or autonomous agent \ architectures
\- Familiarity with prompt engineering, fine\-tuning, and LLM evaluation techniques
\- Knowledge of service mesh, API gateways, or event\-driven architecture on GCP
\- Contributions to open\-source AI\/ML projects or technical communities
\- Experience with Cohere, Anthropic Claude, or Google Gemini
\- Knowledge of testing frameworks for ML systems (unit tests, model validation, A\/B \ testing) \ Tech Stack You Will Work With \ Category \ Platform \ Tools \ GCP
\- Expert proficiency in Python for AI\/ML development (TensorFlow, PyTorch)
\- Hands\-on experience with GCP AI\/ML services (Vertex AI, BigQuery ML, AI Platform, \ AutoML)
\- Strong familiarity with MLOps practices, model versioning, and ML pipeline \ orchestration (Airflow, Kubeflow)
\- Experience building and deploying production AI systems including LLM integration, \ RAG architectures, and vector databases
\- Hands\-on experience with Git, Docker, and Kubernetes for containerized ML \ workloads
\- Excellent problem\-solving skills and a proactive attitude toward learning new AI \ technologies \ Nice to Have
\- Experience with LangChain or other LLM orchestration frameworks
\- Knowledge of vector databases and semantic search
\- Experience with Agentic AI frameworks, ReAct patterns, or autonomous agent \ architectures
\- Familiarity with prompt engineering, fine\-tuning, and LLM evaluation techniques
\- Knowledge of service mesh, API gateways, or event\-driven architecture on GCP
\- Contributions to open\-source AI\/ML projects or technical communities
\- Experience with Cohere, Anthropic Claude, or Google Gemini
\- Knowledge of testing frameworks for ML systems (unit tests, model validation, A\/B \ testing) \ Tech Stack You Will Work With \ Category \ Platform \ Tools \ GCP
(Vertex AI, BigQuery, Data flow, Cloud Functions, Cloud Run, \ Pub\/Sub)
AI\/ML \ Frameworks \ Languages \ Python, TensorFlow, PyTorch, scikit\-learn, Pandas, NumPy, \ LangChain \ Python (primary),
Data & Pipelines BigQuery, Data flow, Apache Airflow, Apache Beam, PySpark \ Observability \ GCP Cloud Operations (Logging, Monitoring, Trace),
New Relic \ CI\/CD \ GitLab, SonarQube, Snyk, GitLeaks \ Containerization Docker, Kubernetes, Cloud Run \ Vector & Search \ Vertex AI Vector Search, Pine cone, BigQuery, Elasticsearch \ LLM Integration \ W
Benefits
Benefits
What We Offer
Competitive\ salaries and comprehensive health benefits
Flexible\ work hours and remote work options.
Professional\ development and training opportunities.
A\ supportive and inclusive work environment